LLM-Driven Algorithm Design for Quantum Circuit Synthesis based on Binary Decision Diagrams
[Sztuczna inteligencja] Autorzy: Yoonju Sim, Federico Berto, Chuanbo Hua i 2 więcej
Quantum circuits are central to implementing quantum algorithms on quantum devices, where quantum gates must be reversible. Many quantum algorithms rely on Boolean functions, which must therefore be implemented reversibly within quantum circuits. Reversible circuit synthesis provides a way to translate such Boolean functions into reversible circuits. Binary decision diagrams (BDDs) offer a scalable approach to this task, but the resulting BDDs and circuits depend heavily on variable ordering. Existing ordering heuristics commonly minimize BDD size because it is closely tied to the circuit size. However, BDD size is an imperfect proxy for the quantum cost of the synthesized circuit (QCC). We propose \texttt{QuantumEvo}, an evolutionary framework that uses an LLM as a heuristic generator for QCC-aware BDD variable ordering. Instead of predicting orderings directly, \texttt{QuantumEvo} sea…
- Kategoria arxiv
- cs.AI
- Kategoria
- Sztuczna inteligencja